Overview

Dataset statistics

Number of variables12
Number of observations2771097
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory253.7 MiB
Average record size in memory96.0 B

Variable types

Numeric12

Alerts

df_index is highly correlated with u and 9 other fieldsHigh correlation
u is highly correlated with df_index and 9 other fieldsHigh correlation
g is highly correlated with df_index and 9 other fieldsHigh correlation
r is highly correlated with df_index and 9 other fieldsHigh correlation
i is highly correlated with df_index and 9 other fieldsHigh correlation
z is highly correlated with df_index and 9 other fieldsHigh correlation
uErr is highly correlated with df_index and 9 other fieldsHigh correlation
gErr is highly correlated with df_index and 9 other fieldsHigh correlation
rErr is highly correlated with df_index and 9 other fieldsHigh correlation
iErr is highly correlated with df_index and 9 other fieldsHigh correlation
zErr is highly correlated with df_index and 9 other fieldsHigh correlation
df_index is highly correlated with u and 6 other fieldsHigh correlation
u is highly correlated with df_index and 5 other fieldsHigh correlation
g is highly correlated with df_index and 7 other fieldsHigh correlation
r is highly correlated with df_index and 7 other fieldsHigh correlation
i is highly correlated with df_index and 6 other fieldsHigh correlation
z is highly correlated with df_index and 6 other fieldsHigh correlation
uErr is highly correlated with u and 2 other fieldsHigh correlation
gErr is highly correlated with df_index and 4 other fieldsHigh correlation
rErr is highly correlated with df_index and 5 other fieldsHigh correlation
zErr is highly correlated with zHigh correlation
df_index is highly correlated with g and 7 other fieldsHigh correlation
u is highly correlated with g and 4 other fieldsHigh correlation
g is highly correlated with df_index and 9 other fieldsHigh correlation
r is highly correlated with df_index and 8 other fieldsHigh correlation
i is highly correlated with df_index and 7 other fieldsHigh correlation
z is highly correlated with df_index and 7 other fieldsHigh correlation
uErr is highly correlated with u and 2 other fieldsHigh correlation
gErr is highly correlated with df_index and 9 other fieldsHigh correlation
rErr is highly correlated with df_index and 8 other fieldsHigh correlation
iErr is highly correlated with df_index and 7 other fieldsHigh correlation
zErr is highly correlated with df_index and 7 other fieldsHigh correlation
df_index is highly correlated with u and 4 other fieldsHigh correlation
u is highly correlated with df_index and 4 other fieldsHigh correlation
g is highly correlated with df_index and 4 other fieldsHigh correlation
r is highly correlated with df_index and 4 other fieldsHigh correlation
i is highly correlated with df_index and 4 other fieldsHigh correlation
z is highly correlated with df_index and 4 other fieldsHigh correlation
uErr is highly correlated with gErrHigh correlation
gErr is highly correlated with uErr and 1 other fieldsHigh correlation
zErr is highly correlated with gErrHigh correlation
iErr is highly skewed (γ1 = 215.8193612) Skewed
zErr is highly skewed (γ1 = 126.8038418) Skewed
df_index is uniformly distributed Uniform
df_index has unique values Unique
ID has unique values Unique

Reproduction

Analysis started2022-02-24 04:35:07.478487
Analysis finished2022-02-24 04:39:09.440038
Duration4 minutes and 1.96 second
Software versionpandas-profiling v3.1.1
Download configurationconfig.json

Variables

df_index
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct2771097
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1385598.454
Minimum0
Maximum2771158
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size21.1 MiB
2022-02-24T01:39:09.482798image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile138573.8
Q1692824
median1385606
Q32078381
95-th percentile2632602.2
Maximum2771158
Range2771158
Interquartile range (IQR)1385557

Descriptive statistics

Standard deviation799958.2458
Coefficient of variation (CV)0.5773377152
Kurtosis-1.199986471
Mean1385598.454
Median Absolute Deviation (MAD)692779
Skewness-2.287114509 × 10-5
Sum3.83962772 × 1012
Variance6.39933195 × 1011
MonotonicityStrictly increasing
2022-02-24T01:39:09.581711image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
01
 
< 0.1%
18474591
 
< 0.1%
18474511
 
< 0.1%
18474521
 
< 0.1%
18474531
 
< 0.1%
18474541
 
< 0.1%
18474551
 
< 0.1%
18474561
 
< 0.1%
18474571
 
< 0.1%
18474581
 
< 0.1%
Other values (2771087)2771087
> 99.9%
ValueCountFrequency (%)
01
< 0.1%
11
< 0.1%
21
< 0.1%
31
< 0.1%
41
< 0.1%
51
< 0.1%
61
< 0.1%
71
< 0.1%
81
< 0.1%
91
< 0.1%
ValueCountFrequency (%)
27711581
< 0.1%
27711571
< 0.1%
27711561
< 0.1%
27711551
< 0.1%
27711541
< 0.1%
27711531
< 0.1%
27711521
< 0.1%
27711511
< 0.1%
27711501
< 0.1%
27711491
< 0.1%

ID
Real number (ℝ≥0)

UNIQUE

Distinct2771097
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.237664767 × 1018
Minimum1.23764588 × 1018
Maximum1.237680531 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.1 MiB
2022-02-24T01:39:09.676922image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1.23764588 × 1018
5-th percentile1.237651538 × 1018
Q11.237658613 × 1018
median1.237663784 × 1018
Q31.237668298 × 1018
95-th percentile1.237679541 × 1018
Maximum1.237680531 × 1018
Range3.465180558 × 1013
Interquartile range (IQR)9.685164491 × 1012

Descriptive statistics

Standard deviation8.395134131 × 1012
Coefficient of variation (CV)6.783043642 × 10-6
Kurtosis-0.5909072918
Mean1.237664767 × 1018
Median Absolute Deviation (MAD)4.663256416 × 1012
Skewness0.3696778269
Sum-3.321424075 × 1018
Variance7.047827708 × 1025
MonotonicityNot monotonic
2022-02-24T01:39:09.770672image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.237671129 × 10181
 
< 0.1%
1.237661434 × 10181
 
< 0.1%
1.237671143 × 10181
 
< 0.1%
1.237678879 × 10181
 
< 0.1%
1.237663916 × 10181
 
< 0.1%
1.23765125 × 10181
 
< 0.1%
1.237664294 × 10181
 
< 0.1%
1.237678663 × 10181
 
< 0.1%
1.237665329 × 10181
 
< 0.1%
1.237679323 × 10181
 
< 0.1%
Other values (2771087)2771087
> 99.9%
ValueCountFrequency (%)
1.23764588 × 10181
< 0.1%
1.23764588 × 10181
< 0.1%
1.23764588 × 10181
< 0.1%
1.23764588 × 10181
< 0.1%
1.23764588 × 10181
< 0.1%
1.23764588 × 10181
< 0.1%
1.23764588 × 10181
< 0.1%
1.23764588 × 10181
< 0.1%
1.23764588 × 10181
< 0.1%
1.23764588 × 10181
< 0.1%
ValueCountFrequency (%)
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%

u
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct862294
Distinct (%)31.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.54721891
Minimum7.918076
Maximum33.45042
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.1 MiB
2022-02-24T01:39:09.864422image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum7.918076
5-th percentile18.744108
Q120.68293
median22.81069
Q324.18341
95-th percentile26.06424
Maximum33.45042
Range25.532344
Interquartile range (IQR)3.50048

Descriptive statistics

Standard deviation2.279702953
Coefficient of variation (CV)0.1011079443
Kurtosis-0.6206763375
Mean22.54721891
Median Absolute Deviation (MAD)1.62961
Skewness-0.2604099229
Sum62480530.68
Variance5.197045552
MonotonicityNot monotonic
2022-02-24T01:39:09.947567image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24.63466363
 
< 0.1%
24.63467315
 
< 0.1%
24.63465259
 
< 0.1%
24.63468224
 
< 0.1%
24.63469101
 
< 0.1%
24.634773
 
< 0.1%
24.6346471
 
< 0.1%
24.6347132
 
< 0.1%
24.6346324
 
< 0.1%
24.6347222
 
< 0.1%
Other values (862284)2769613
99.9%
ValueCountFrequency (%)
7.9180761
< 0.1%
9.8665341
< 0.1%
9.9419421
< 0.1%
10.170251
< 0.1%
10.227171
< 0.1%
10.488951
< 0.1%
10.541811
< 0.1%
11.06431
< 0.1%
11.213971
< 0.1%
11.417541
< 0.1%
ValueCountFrequency (%)
33.450421
< 0.1%
32.666631
< 0.1%
31.771321
< 0.1%
31.386641
< 0.1%
31.107921
< 0.1%
30.961
< 0.1%
30.813441
< 0.1%
30.779911
< 0.1%
30.773581
< 0.1%
30.760491
< 0.1%

g
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct771107
Distinct (%)27.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.85631799
Minimum7.466997
Maximum33.72469
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.1 MiB
2022-02-24T01:39:10.051802image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum7.466997
5-th percentile17.24249
Q118.798
median21.5492
Q322.42596
95-th percentile23.561882
Maximum33.72469
Range26.257693
Interquartile range (IQR)3.62796

Descriptive statistics

Standard deviation2.120288897
Coefficient of variation (CV)0.1016617074
Kurtosis-0.6362952592
Mean20.85631799
Median Absolute Deviation (MAD)1.22676
Skewness-0.5167377968
Sum57794880.23
Variance4.495625009
MonotonicityNot monotonic
2022-02-24T01:39:10.148803image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25.11438108
 
< 0.1%
25.1143766
 
< 0.1%
25.1143957
 
< 0.1%
25.114445
 
< 0.1%
22.256925
 
< 0.1%
22.1497725
 
< 0.1%
22.0357224
 
< 0.1%
22.2307123
 
< 0.1%
22.1149323
 
< 0.1%
22.1995623
 
< 0.1%
Other values (771097)2770678
> 99.9%
ValueCountFrequency (%)
7.4669971
< 0.1%
9.8970961
< 0.1%
10.246591
< 0.1%
10.327731
< 0.1%
10.407441
< 0.1%
10.533391
< 0.1%
10.640631
< 0.1%
10.754631
< 0.1%
11.100781
< 0.1%
11.156871
< 0.1%
ValueCountFrequency (%)
33.724691
< 0.1%
32.909441
< 0.1%
32.149971
< 0.1%
31.670361
< 0.1%
31.602241
< 0.1%
31.523151
< 0.1%
31.354171
< 0.1%
31.327361
< 0.1%
31.066181
< 0.1%
30.953071
< 0.1%

r
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct701819
Distinct (%)25.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.52907862
Minimum8.902843
Maximum22.99995
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.1 MiB
2022-02-24T01:39:10.247801image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum8.902843
5-th percentile16.43614
Q117.74942
median20.05909
Q320.93971
95-th percentile22.10703
Maximum22.99995
Range14.097107
Interquartile range (IQR)3.19029

Descriptive statistics

Standard deviation1.868157141
Coefficient of variation (CV)0.09566028066
Kurtosis-0.7443979195
Mean19.52907862
Median Absolute Deviation (MAD)1.34901
Skewness-0.4281007916
Sum54116971.16
Variance3.490011105
MonotonicityNot monotonic
2022-02-24T01:39:10.343811image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20.550723
 
< 0.1%
20.2904522
 
< 0.1%
20.5256322
 
< 0.1%
20.5042522
 
< 0.1%
20.7846122
 
< 0.1%
20.6164622
 
< 0.1%
20.4497522
 
< 0.1%
20.7174522
 
< 0.1%
20.4366422
 
< 0.1%
20.6365822
 
< 0.1%
Other values (701809)2770876
> 99.9%
ValueCountFrequency (%)
8.9028431
< 0.1%
9.4744761
< 0.1%
9.5015741
< 0.1%
9.8482581
< 0.1%
9.9037461
< 0.1%
9.9209511
< 0.1%
10.044621
< 0.1%
10.072471
< 0.1%
10.109561
< 0.1%
10.131251
< 0.1%
ValueCountFrequency (%)
22.999951
< 0.1%
22.999941
< 0.1%
22.999932
< 0.1%
22.999911
< 0.1%
22.99991
< 0.1%
22.999812
< 0.1%
22.99981
< 0.1%
22.999731
< 0.1%
22.999711
< 0.1%
22.999681
< 0.1%

i
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct684990
Distinct (%)24.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.7975133
Minimum8.364965
Maximum31.65274
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.1 MiB
2022-02-24T01:39:10.447174image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum8.364965
5-th percentile16.020778
Q117.3165
median19.17881
Q319.91382
95-th percentile21.4056
Maximum31.65274
Range23.287775
Interquartile range (IQR)2.59732

Descriptive statistics

Standard deviation1.682664926
Coefficient of variation (CV)0.0895152938
Kurtosis-0.3469783265
Mean18.7975133
Median Absolute Deviation (MAD)1.14515
Skewness-0.3030799236
Sum52089732.72
Variance2.831361252
MonotonicityNot monotonic
2022-02-24T01:39:10.536701image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24.361878
 
< 0.1%
24.3618147
 
< 0.1%
19.7492827
 
< 0.1%
19.52326
 
< 0.1%
19.6674526
 
< 0.1%
19.6128326
 
< 0.1%
19.644525
 
< 0.1%
19.5481925
 
< 0.1%
19.5657325
 
< 0.1%
19.6903725
 
< 0.1%
Other values (684980)2770767
> 99.9%
ValueCountFrequency (%)
8.3649651
< 0.1%
8.4112851
< 0.1%
9.3708691
< 0.1%
9.5270821
< 0.1%
9.5500071
< 0.1%
9.5687771
< 0.1%
9.754041
< 0.1%
9.850521
< 0.1%
9.8860051
< 0.1%
9.9305741
< 0.1%
ValueCountFrequency (%)
31.652741
< 0.1%
31.231631
< 0.1%
31.149821
< 0.1%
31.073351
< 0.1%
30.846291
< 0.1%
30.831511
< 0.1%
30.711051
< 0.1%
30.652091
< 0.1%
30.576231
< 0.1%
30.498611
< 0.1%

z
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct683963
Distinct (%)24.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.39512669
Minimum6.485586
Maximum30.01704
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.1 MiB
2022-02-24T01:39:10.626358image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum6.485586
5-th percentile15.70244
Q117.02607
median18.72149
Q319.44233
95-th percentile21.12195
Maximum30.01704
Range23.531454
Interquartile range (IQR)2.41626

Descriptive statistics

Standard deviation1.646698893
Coefficient of variation (CV)0.08951821429
Kurtosis0.02160338546
Mean18.39512669
Median Absolute Deviation (MAD)1.01411
Skewness-0.1468942164
Sum50974680.37
Variance2.711617243
MonotonicityNot monotonic
2022-02-24T01:39:10.714933image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22.8269569
 
< 0.1%
22.82691330
 
< 0.1%
22.82689170
 
< 0.1%
22.8269289
 
< 0.1%
22.8269341
 
< 0.1%
22.8269431
 
< 0.1%
19.1792929
 
< 0.1%
19.2171628
 
< 0.1%
19.2534428
 
< 0.1%
19.1566227
 
< 0.1%
Other values (683953)2769755
> 99.9%
ValueCountFrequency (%)
6.4855861
< 0.1%
6.9728551
< 0.1%
7.1403881
< 0.1%
7.2817191
< 0.1%
9.5631221
< 0.1%
9.6733111
< 0.1%
9.7591461
< 0.1%
9.7711581
< 0.1%
9.9718491
< 0.1%
9.9871541
< 0.1%
ValueCountFrequency (%)
30.017041
< 0.1%
29.383741
< 0.1%
29.263141
< 0.1%
29.183741
< 0.1%
29.174081
< 0.1%
29.041691
< 0.1%
29.039351
< 0.1%
29.01941
< 0.1%
28.966261
< 0.1%
28.917931
< 0.1%

uErr
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2426278
Distinct (%)87.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6795658449
Minimum0.0001527219
Maximum68.59662
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.1 MiB
2022-02-24T01:39:10.812935image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0.0001527219
5-th percentile0.034038648
Q10.1267589
median0.5586478
Q31.03992
95-th percentile1.7884246
Maximum68.59662
Range68.59646728
Interquartile range (IQR)0.9131611

Descriptive statistics

Standard deviation0.6173188602
Coefficient of variation (CV)0.9084018346
Kurtosis128.3319909
Mean0.6795658449
Median Absolute Deviation (MAD)0.4472315
Skewness3.055100909
Sum1883142.874
Variance0.3810825751
MonotonicityNot monotonic
2022-02-24T01:39:10.906936image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.208498
 
< 0.1%
1.1764178
 
< 0.1%
1.1518958
 
< 0.1%
1.0406248
 
< 0.1%
1.0697638
 
< 0.1%
1.1366498
 
< 0.1%
1.0185938
 
< 0.1%
1.0438837
 
< 0.1%
1.3300097
 
< 0.1%
1.0773357
 
< 0.1%
Other values (2426268)2771020
> 99.9%
ValueCountFrequency (%)
0.00015272191
< 0.1%
0.00025310871
< 0.1%
0.00059578531
< 0.1%
0.00063232911
< 0.1%
0.0013525921
< 0.1%
0.0015262641
< 0.1%
0.0021296481
< 0.1%
0.0022865361
< 0.1%
0.0024110081
< 0.1%
0.0024351181
< 0.1%
ValueCountFrequency (%)
68.596621
< 0.1%
55.509481
< 0.1%
46.498841
< 0.1%
40.798731
< 0.1%
39.446211
< 0.1%
38.201951
< 0.1%
36.878481
< 0.1%
30.99551
< 0.1%
28.227461
< 0.1%
27.371091
< 0.1%

gErr
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2400035
Distinct (%)86.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1352228852
Minimum0.0002041792
Maximum41.14543
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.1 MiB
2022-02-24T01:39:11.011259image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0.0002041792
5-th percentile0.0055366346
Q10.01317563
median0.09019641
Q30.1729824
95-th percentile0.45140432
Maximum41.14543
Range41.14522582
Interquartile range (IQR)0.15980677

Descriptive statistics

Standard deviation0.1912511815
Coefficient of variation (CV)1.41434034
Kurtosis1938.599197
Mean0.1352228852
Median Absolute Deviation (MAD)0.0779491
Skewness14.75855721
Sum374715.7316
Variance0.03657701441
MonotonicityNot monotonic
2022-02-24T01:39:11.097600image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.13267847
 
< 0.1%
0.11799877
 
< 0.1%
0.12248727
 
< 0.1%
0.15744127
 
< 0.1%
0.1281867
 
< 0.1%
0.12239377
 
< 0.1%
0.12826567
 
< 0.1%
0.11705747
 
< 0.1%
0.14582817
 
< 0.1%
0.14000947
 
< 0.1%
Other values (2400025)2771027
> 99.9%
ValueCountFrequency (%)
0.00020417921
< 0.1%
0.0003442481
< 0.1%
0.00037442561
< 0.1%
0.00041113421
< 0.1%
0.00045212181
< 0.1%
0.00051167571
< 0.1%
0.00052219471
< 0.1%
0.00054079661
< 0.1%
0.0005696471
< 0.1%
0.00061961981
< 0.1%
ValueCountFrequency (%)
41.145431
< 0.1%
40.807771
< 0.1%
27.876591
< 0.1%
25.203171
< 0.1%
18.666031
< 0.1%
16.810181
< 0.1%
14.33141
< 0.1%
13.896031
< 0.1%
13.569331
< 0.1%
12.596771
< 0.1%

rErr
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2512717
Distinct (%)90.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.05601202525
Minimum0.0002880982
Maximum14.52429
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.1 MiB
2022-02-24T01:39:11.188607image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0.0002880982
5-th percentile0.004357691
Q10.008711451
median0.03777351
Q30.07395164
95-th percentile0.1807854
Maximum14.52429
Range14.5240019
Interquartile range (IQR)0.065240189

Descriptive statistics

Standard deviation0.06815684939
Coefficient of variation (CV)1.216825299
Kurtosis1299.620031
Mean0.05601202525
Median Absolute Deviation (MAD)0.029997709
Skewness11.73245242
Sum155214.7551
Variance0.004645356119
MonotonicityNot monotonic
2022-02-24T01:39:11.282552image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.10173526
 
< 0.1%
0.10314316
 
< 0.1%
0.13498716
 
< 0.1%
0.10848296
 
< 0.1%
0.10297356
 
< 0.1%
0.12780866
 
< 0.1%
0.10304226
 
< 0.1%
0.046955466
 
< 0.1%
0.15797216
 
< 0.1%
0.10091136
 
< 0.1%
Other values (2512707)2771037
> 99.9%
ValueCountFrequency (%)
0.00028809821
< 0.1%
0.00029452961
< 0.1%
0.00032062281
< 0.1%
0.00035198211
< 0.1%
0.00037071751
< 0.1%
0.00037074071
< 0.1%
0.00037470931
< 0.1%
0.00038703781
< 0.1%
0.00041203841
< 0.1%
0.00048491931
< 0.1%
ValueCountFrequency (%)
14.524291
< 0.1%
9.040691
< 0.1%
8.5569411
< 0.1%
8.4200181
< 0.1%
7.7123911
< 0.1%
7.4970261
< 0.1%
7.2769151
< 0.1%
5.5287411
< 0.1%
5.5018441
< 0.1%
5.1243161
< 0.1%

iErr
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
SKEWED

Distinct2458972
Distinct (%)88.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.04065202339
Minimum4.2032 × 10-6
Maximum55.15096
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.1 MiB
2022-02-24T01:39:11.384865image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum4.2032 × 10-6
5-th percentile0.004368665
Q10.008751572
median0.02717371
Q30.04588228
95-th percentile0.13778706
Maximum55.15096
Range55.1509558
Interquartile range (IQR)0.037130708

Descriptive statistics

Standard deviation0.09732236877
Coefficient of variation (CV)2.394035048
Kurtosis97945.76804
Mean0.04065202339
Median Absolute Deviation (MAD)0.018491108
Skewness215.8193612
Sum112650.7001
Variance0.009471643463
MonotonicityNot monotonic
2022-02-24T01:39:11.453454image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.02938737
 
< 0.1%
0.010496116
 
< 0.1%
0.010463096
 
< 0.1%
0.034087776
 
< 0.1%
0.030170656
 
< 0.1%
0.018892266
 
< 0.1%
0.010998246
 
< 0.1%
0.036484336
 
< 0.1%
0.011324526
 
< 0.1%
0.10697866
 
< 0.1%
Other values (2458962)2771036
> 99.9%
ValueCountFrequency (%)
4.2032 × 10-61
< 0.1%
0.00024163631
< 0.1%
0.00026542121
< 0.1%
0.00026559841
< 0.1%
0.00033388491
< 0.1%
0.00035752271
< 0.1%
0.00036297211
< 0.1%
0.00040605161
< 0.1%
0.00043487741
< 0.1%
0.00044301361
< 0.1%
ValueCountFrequency (%)
55.150961
< 0.1%
52.32151
< 0.1%
48.506161
< 0.1%
28.03321
< 0.1%
26.415021
< 0.1%
20.709491
< 0.1%
19.052051
< 0.1%
16.700471
< 0.1%
16.665321
< 0.1%
14.793831
< 0.1%

zErr
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED

Distinct2398599
Distinct (%)86.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1033954568
Minimum0.0001718631
Maximum125.6025
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.1 MiB
2022-02-24T01:39:11.574787image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0.0001718631
5-th percentile0.0093098
Q10.0226173
median0.06647153
Q30.1130222
95-th percentile0.36526564
Maximum125.6025
Range125.6023281
Interquartile range (IQR)0.0904049

Descriptive statistics

Standard deviation0.2099898371
Coefficient of variation (CV)2.030938724
Kurtosis55879.59457
Mean0.1033954568
Median Absolute Deviation (MAD)0.04462286
Skewness126.8038418
Sum286518.8402
Variance0.04409573171
MonotonicityNot monotonic
2022-02-24T01:39:11.674787image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.10690089
 
< 0.1%
0.10701118
 
< 0.1%
0.104168
 
< 0.1%
0.10692928
 
< 0.1%
0.1018178
 
< 0.1%
0.11966128
 
< 0.1%
0.1041018
 
< 0.1%
0.11875778
 
< 0.1%
0.10383198
 
< 0.1%
0.12270177
 
< 0.1%
Other values (2398589)2771017
> 99.9%
ValueCountFrequency (%)
0.00017186311
< 0.1%
0.000204251
< 0.1%
0.00022468031
< 0.1%
0.00045838071
< 0.1%
0.00047351351
< 0.1%
0.00097596651
< 0.1%
0.0010065591
< 0.1%
0.0010185741
< 0.1%
0.0010790471
< 0.1%
0.0011199091
< 0.1%
ValueCountFrequency (%)
125.60251
< 0.1%
70.744061
< 0.1%
51.205181
< 0.1%
48.380921
< 0.1%
43.065531
< 0.1%
38.727211
< 0.1%
35.620291
< 0.1%
33.705261
< 0.1%
28.623171
< 0.1%
28.584331
< 0.1%

Interactions

2022-02-24T01:38:50.566164image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:36:47.330120image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:36:58.351188image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:09.904966image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:21.370672image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:32.743807image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:44.194022image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:55.573851image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:06.907456image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:17.883395image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:28.805318image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:39.707165image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:51.495424image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:36:48.245178image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:36:59.300762image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:10.876457image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:22.329944image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:33.714645image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:45.151886image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:56.528873image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:07.835227image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:18.792451image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:29.738508image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:40.617402image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:52.403981image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:36:49.174941image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:00.285246image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:11.830867image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:23.284479image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:34.681726image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:46.111163image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:57.499338image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:08.770257image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:19.706562image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:30.663620image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:41.547502image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:53.314532image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:36:50.095362image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:01.254549image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:12.797687image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:24.231923image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:35.643754image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:47.059714image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:58.442562image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:09.684994image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:20.620390image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:31.577616image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:42.445115image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:54.228750image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:36:51.019714image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:02.225157image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:13.759847image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:25.174814image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:36.588752image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:48.009753image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:59.387868image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:10.626371image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:21.537734image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:32.485519image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:43.361195image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:55.145683image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:36:51.944827image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:03.199080image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:14.725395image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:26.126774image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:37.552281image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:48.947173image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:00.344957image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:11.540407image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:22.443032image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:33.399598image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:44.284854image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:56.053352image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:36:52.864343image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:04.169092image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:15.683867image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:27.074378image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:38.512626image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:49.895924image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:01.290396image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:12.467114image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:23.364911image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:34.309810image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:45.198558image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:56.949814image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:36:53.768582image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:05.122348image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:16.627542image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:28.022511image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:39.457047image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:50.824203image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:02.233552image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:13.366775image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:24.273405image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:35.207649image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:46.083670image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:57.853593image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:36:54.679065image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:06.084653image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:17.583989image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:28.970027image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:40.412112image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:51.764727image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:03.178919image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:14.269216image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:25.178615image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:36.104734image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:46.995034image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:58.747270image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:36:55.577776image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:07.036699image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:18.529569image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:29.897345image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:41.357227image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:52.702353image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:04.107167image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:15.168449image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:26.064277image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:37.002159image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:47.888284image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:59.658710image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:36:56.484348image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:07.997581image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:19.481206image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:30.841346image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:42.311686image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:53.663835image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:05.049406image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:16.073359image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:26.990012image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:37.896705image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:48.775940image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:39:00.551874image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:36:57.385050image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:08.951529image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:20.434977image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:31.784402image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:43.259911image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:37:54.621648image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:06.010401image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:16.965474image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:27.895268image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:38.794229image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T01:38:49.671198image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Correlations

2022-02-24T01:39:11.759784image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-02-24T01:39:11.875784image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-02-24T01:39:12.001534image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-02-24T01:39:12.105066image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-02-24T01:39:00.705824image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
A simple visualization of nullity by column.
2022-02-24T01:39:01.888219image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

First rows

df_indexIDugrizuErrgErrrErriErrzErr
00123767112912568392024.7015222.3056021.7447421.4008021.423480.7816860.0989800.0782200.0823700.240668
11123765777231439497822.6739721.9668621.9489921.7237921.861050.3908180.0776080.1287820.1721280.565489
22123766076483240050326.1858622.4151621.6536121.5735521.896040.3711850.1113130.0796660.1036730.496207
33123766558433457054624.6047121.8725621.6543221.6429122.185190.8269980.0607780.0652660.1001260.507707
44123765719090430005925.1216422.7999622.2114621.8542522.102070.6820360.1339500.1111800.1120900.480457
55123766354314487476924.0921022.8534622.3076322.0479022.402830.6423210.1290140.1242500.1358430.529423
66123768050343346338123.9805424.2461822.7301321.3028819.857081.7011480.9327390.4797800.1942790.188464
77123766829821027949624.1753326.8435220.1388918.7263621.075542.5584260.6756040.0615690.0603170.877250
88123765787700074992021.8025020.7598820.2154620.1375420.198180.1385950.0319380.0255080.0320240.116473
99123766835028433354125.3014921.9747421.2539121.1610821.161520.6452500.0788750.0527450.0676740.213721

Last rows

df_indexIDugrizuErrgErrrErriErrzErr
27710872771149123768010024078618823.0586922.3616821.5330321.1167020.319470.6016640.1368260.1198760.1135210.223924
27710882771150123766230297811400521.7140321.3723920.9356320.7153620.445280.1256910.0412730.0406240.0468670.112831
27710892771151123765861197702850024.8257123.1388621.5402620.3089519.378262.8694780.5842350.2025270.0991330.153437
27710902771152123766558432709866319.9325219.6159419.4306319.4592019.334380.0395150.0130050.0135620.0194020.055167
27710912771153123767879081728422420.0775419.6628719.6089819.6364720.096040.0559200.0145540.0196430.0271990.162892
27710922771154123766970105115466921.6929121.8026821.3754721.3653921.507890.2055820.0915140.1093650.1641780.592550
27710932771155123765153548383051321.1295221.3159621.4913421.1873620.980130.1024430.0561570.0891180.1017490.310130
27710942771156123768031122980945022.0768521.7965721.4865921.4014620.842150.2322130.0568640.0763200.1003190.263959
27710952771157123766146383622995221.2660120.7593120.5711120.4226220.526660.0857250.0247490.0283260.0337300.121159
27710962771158123764992004358185222.5910921.2713920.8219920.6160720.615850.3059510.0481920.0457080.0556660.222432